Authors :
Atinuke Yusuf; Daniel Ugbomoiko; David Temitope Ogunleye; Olufisayo Famuyiwa; Chika Aladeokin; Elizabeth Abodunrin
Volume/Issue :
Volume 11 - 2026, Issue 3 - March
Google Scholar :
https://tinyurl.com/8u7ubxwj
Scribd :
https://tinyurl.com/k7wavyjn
DOI :
https://doi.org/10.38124/ijisrt/26mar526
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Background:
Dyslipidemia is a central and modifiable cardiovascular risk factor; however, its characterization alongside systemic
inflammation, cardiac biomarkers, and renal dysfunction in Nigerian community-dwelling populations remains limited.
This study investigated the atherogenic lipid profile and its role within an integrated cardiovascular risk pathway among
residents of Ibadan North Local Government, Ibadan, Nigeria.
Methods:
A cross-sectional study enrolled 265 participants selected by stratified random sampling from Ibadan North Local
Government. Fasting blood samples were analyzed for total cholesterol (TC), triglycerides (TG), high-density lipoprotein
cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Inflammatory markers (C-reactive protein [CRP]
and interleukin-6 [IL-6]), cardiac biomarkers (Troponin I and CK-MB), and renal function parameters (creatinine and
urea) were also assessed. Sociodemographic and lifestyle data were obtained via structured questionnaires. Multiple linear
regression and descriptive statistics were applied; significance was set at p < 0.05.
Results:
The mean TC was 206.16 ± 44.57 mg/dL (borderline high), mean LDL-C was 128.05 ± 39.54 mg/dL (borderline high),
mean TG was 109.22 ± 37.17 mg/dL (normal), and mean HDL-C was 54.37 ± 11.27 mg/dL. Alcohol consumption significantly
increased dyslipidemia risk (β = 0.221, p < 0.05), while regular exercise was protective (β = −0.379, p < 0.05). In the integrated
regression model, dyslipidemia was the strongest independent predictor of cardiovascular risk (β = −0.417, t = −7.407, p <
0.05), followed by elevated Troponin I (β = 0.466, p < 0.05). The full model including demographic and biochemical
predictors explained 37.6% of variance in cardiovascular risk (R² = 0.376), with gender (male sex) and systemic
inflammation also achieving significance.
Conclusion:
Dyslipidemia, particularly borderline-high LDL-C and TC, is prevalent and constitutes the dominant biochemical
driver of cardiovascular risk in this population. Its synergism with systemic inflammation and subclinical cardiac injury
highlights the need for integrated lipid-inflammatory screening programs and targeted lifestyle interventions in Ibadan
North.
Keywords :
Dyslipidemia; Lipid Profile; Cardiovascular Risk; C-Reactive Protein; Interleukin-6; Troponin I; Nigeria.
References :
- Apple FS, Murakami MM, Pearce LA, Herzog CA (2002). Predictive value of cardiac troponin I and T for subsequent death in end-stage renal disease. Circulation, 106(23):2941–2945.
- Banerjee A, et al. (2024). Trends in cardiovascular disease mortality in sub-Saharan Africa. Lancet Global Health.
- Benjamin EJ, Muntner P, Alonso A, et al. (2019). Heart Disease and Stroke Statistics — 2019 Update. Circulation, 139(10): e56–e528.
- Ference BA, et al. (2017). Low-density lipoproteins cause atherosclerotic cardiovascular disease. European Heart Journal, 38(32):2459–2472.
- Finegold JA, et al. (2023). Sex differences in cardiovascular risk and outcomes. BMC Medicine.
- Grundy SM, et al. (2019). 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol. Journal of the American College of Cardiology, 73(24): e285–e350.
- Kokkinos P, Myers J (2010). Exercise and physical activity: clinical outcomes and applications. Circulation, 122(16):1637–1648.
- Miller M, et al. (2011). Triglycerides and cardiovascular disease: a scientific statement from the American Heart Association. Circulation, 123(20):2292–2333.
- O'Keefe JH, Bell DS (2007). Postprandial hyperglycemia/hyperlipidemia is a cardiovascular risk factor. American Journal of Cardiology, 100(5):899–904.
- Ogah OS, et al. (2018). Burden of heart disease and use of cardiovascular procedures in Nigeria. Cardiovascular Journal of Africa, 29(3):180–185.
- Odunyemi OA, et al. (2023). Non-communicable disease burden in Nigeria: epidemiology and policy implications. Nigerian Journal of Clinical Practice.
- Olvera Lopez E, et al. (2023). Cardiovascular disease. StatPearls Publishing.
- Packard C (2006). Small dense low-density lipoprotein and its role as an independent predictor of cardiovascular disease. Current Opinion in Lipidology, 17(4):412–417.
- Pearson TA, et al. (2003). Markers of inflammation and cardiovascular disease. Circulation, 107(3):499–511.
- Popkin BM, et al. (2012). Now and then: the global nutrition transition. Nutrition Reviews, 70(Suppl. 1): S3–S4.
- Ridker PM, et al. (2000). Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events. New England Journal of Medicine, 347(20):836–843.
- WHO (2025). Cardiovascular diseases fact sheet. Geneva: World Health Organization.
Background:
Dyslipidemia is a central and modifiable cardiovascular risk factor; however, its characterization alongside systemic
inflammation, cardiac biomarkers, and renal dysfunction in Nigerian community-dwelling populations remains limited.
This study investigated the atherogenic lipid profile and its role within an integrated cardiovascular risk pathway among
residents of Ibadan North Local Government, Ibadan, Nigeria.
Methods:
A cross-sectional study enrolled 265 participants selected by stratified random sampling from Ibadan North Local
Government. Fasting blood samples were analyzed for total cholesterol (TC), triglycerides (TG), high-density lipoprotein
cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). Inflammatory markers (C-reactive protein [CRP]
and interleukin-6 [IL-6]), cardiac biomarkers (Troponin I and CK-MB), and renal function parameters (creatinine and
urea) were also assessed. Sociodemographic and lifestyle data were obtained via structured questionnaires. Multiple linear
regression and descriptive statistics were applied; significance was set at p < 0.05.
Results:
The mean TC was 206.16 ± 44.57 mg/dL (borderline high), mean LDL-C was 128.05 ± 39.54 mg/dL (borderline high),
mean TG was 109.22 ± 37.17 mg/dL (normal), and mean HDL-C was 54.37 ± 11.27 mg/dL. Alcohol consumption significantly
increased dyslipidemia risk (β = 0.221, p < 0.05), while regular exercise was protective (β = −0.379, p < 0.05). In the integrated
regression model, dyslipidemia was the strongest independent predictor of cardiovascular risk (β = −0.417, t = −7.407, p <
0.05), followed by elevated Troponin I (β = 0.466, p < 0.05). The full model including demographic and biochemical
predictors explained 37.6% of variance in cardiovascular risk (R² = 0.376), with gender (male sex) and systemic
inflammation also achieving significance.
Conclusion:
Dyslipidemia, particularly borderline-high LDL-C and TC, is prevalent and constitutes the dominant biochemical
driver of cardiovascular risk in this population. Its synergism with systemic inflammation and subclinical cardiac injury
highlights the need for integrated lipid-inflammatory screening programs and targeted lifestyle interventions in Ibadan
North.
Keywords :
Dyslipidemia; Lipid Profile; Cardiovascular Risk; C-Reactive Protein; Interleukin-6; Troponin I; Nigeria.